Indermohan (Inder) S. Monga serves as the Division Director for Scientific Networking Division, Lawrence Berkeley National Lab and Executive Director of Energy Sciences Network, a high-performance network user facility optimized for large-scale science, interconnecting the National Laboratory System in the United States. In addition to managing the organization, his efforts are directed towards advancing the science of networking for collaborative and distributed research applications, as well as contributing to ongoing research projects tackling programmability, analytics and quality of experience driving convergence between application layer and the network. He currently holds 23 patents and has 20+ years of industry and research experience in telecommunications and data networking. His work experience in the private sector includes network engineering for Wellfleet Communications, Bay Networks and Nortel where he focused on application and network convergence. His undergraduate degree is in electrical/electronics engineering from Indian Institute of Technology in Kanpur, India, with graduate studies in computer engineering from Boston University.
Inder Monga, Chin Guok, John MacAuley, Alex Sim, Harvey Newman, Justas Balcas, Phil DeMar, Linda Winkler, Tom Lehman, Xi Yang, “Software-Defined Network for End-to-end Networked Science at the Exascale”, Future Generation Computer Systems, April 13, 2020,
Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end-to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.
Marco Ruffini, Kasandra Pillay, Chongjin Xie, Lei Shi, Dale Smith, Inder Monga, Xinsheng Wang, and Jun Shan Wey, “Connected OFCity Challenge: Addressing the Digital Divide in the Developing World”, Journal of Optical Communications and Networking, June 20, 2019, 11:354-361,
Jonathan B. Ajo-Franklin, Shan Dou, Nathaniel J. Lindsey, Inder Monga, Chris Tracy, Michelle Robertson, Veronica Rodriguez Tribaldos, Craig Ulrich, Barry Freifeld, Thomas Daley and Xiaoye Li, “Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection”, Nature, February 4, 2019,
RK Shyamasundar, Prabhat Prabhat, Vipin Chaudhary, Ashwin Gumaste, Inder Monga, Vishwas Patil, Ankur Narang, “Computing for Science, Engineering and Society: Challenges, Requirement, and Strategic Roadmap”, Proceedings of the Indian National Science Academy, June 15, 2018,
Inder Monga, Prabhat, “Big-Data Science: Infrastructure Impact”, Proceedings of the Indian National Science Academy, June 15, 2018,
The nature of science is changing dramatically, from single researcher at a lab or university laboratory working with graduate students to a distributed multi- researcher consortiums, across universities and research labs, tackling large scientific problems. In addition, experimentalists and theorists are collaborating with each other by designing experiments to prove the proposed theories. ‘Big Data’ being produced by these large experiments have to verified against simulations run on High Performance Computing (HPC) resources.
The trends above are pointing towards
Geographically dispersed experiments (and associated communities) that require data being moved across multiple sites. Appropriate mechanisms and tools need to be employed to move, store and archive datasets from such experiments.
Convergence of simulation (requiring High Performance Computing) and Big Data Analytics (requiring advanced on-site data management techniques) into a small number of High Performance Computing centers. Such centers are key for consolidating software and hardware infrastructure efforts, and achieving broad impact across numerous scientific domains.
The trends indicate that for modern science and scientific discovery, infrastructure support for handling both large scientific data as well as high-performance computing is extremely important. In addition, given the distributed nature of research and big-team science, it is important to build infrastructure, both hardware and software, that enables sharing across
institutions, researchers, students, industry and academia. This is the only way that a nation can maximize the research capabilities of its citizens while maximizing the use of its investments in computer, storage, network and experimental infrastructure.
This chapter introduces infrastructure requirements of High-Performance Computing and Networking with examples drawn from NERSC and ESnet, two large Department of Energy facilities at Lawrence Berkeley National Laboratory, CA, USA, that exemplify some of the qualities needed for future Research & Education infrastructure.
Ilya Baldin, Tilman Wolf, “The Future of CISE Distributed Research Infrastructure”, ACM SIGCOMM Computer Communication Review, May 1, 2018,
Shared research infrastructure that is globally distributed and widely accessible has been a hallmark of the networking community. We present a vision for a future mid-scale distributed research infrastructure aimed at enabling new types of discoveries. The “lessons learned” from constructing and operating the Global Environment for Network Innovations (GENI) infrastructure are the basis for our attempt to project future concepts and solutions. Our aim is to engage the community to contribute new ideas and to inform funding agencies about future research directions.
M Kiran, E Pouyoul, A Mercian, B Tierney, C Guok, I Monga, “Enabling intent to configure scientific networks for high performance demands”, Future Generation Computer Systems, August 2, 2017,
Kim Roberts, Qunbi Zhuge, Inder Monga, Sebastien Gareau, and Charles Laperle, “Beyond 100 Gb/s: Capacity, Flexibility, and Network Optimization”, Journal of Optical Communication Network, April 1, 2017, Volume 9,
- Download File: Beyond-100Gbs-Capacity-Flexibility-and-Network-Optimization.pdf (pdf: 2.1 MB)
In this paper, we discuss building blocks that enable the exploitation of optical capacities beyond 100 Gb∕s. Optical networks will benefit from more flexibility and agility in their network elements, especially from co- herent transceivers. To achieve capacities of 400 Gb∕s and more, coherent transceivers will operate at higher symbol rates. This will be made possible with higher bandwidth components using new electro-optic technologies imple- mented with indium phosphide and silicon photonics. Digital signal processing will benefit from new algorithms. Multi-dimensional modulation, of which some formats are already in existence in current flexible coherent transceiv- ers, will provide improved tolerance to noise and fiber non- linearities. Constellation shaping will further improve these tolerances while allowing a finer granularity in the selection of capacity. Frequency-division multiplexing will also provide improved tolerance to the nonlinear charac- teristics of fibers. Algorithms with reduced computation complexity will allow the implementation, at speeds, of direct pre-compensation of nonlinear propagation effects. Advancement in forward error correction will shrink the performance gap with Shannon’s limit. At the network con- trol and management level, new tools are being developed to achieve a more efficient utilization of networks. This will also allow for network virtualization, orchestration, and management. Finally, FlexEthernet and FlexOTN will be put in place to allow network operators to optimize capac- ity in their optical transport networks without manual changes to the client hardware.
Ashwin Gumaste, Tamal Das, Kandarp Khandwala, and Inder Monga, “Network Hardware Virtualization for Application Provisioning in Core Networks”, IEEE Communications Magazine, February 1, 2017,
- Download File: HW-Virt.pdf (pdf: 241 KB)
Service providers and vendors are moving toward a network virtualized core, whereby multiple applications would be treated on their own merit in programmable hardware. Such a network would have the advantage of being customized for user requirements and allow provisioning of next generation services that are built speci cally to meet user needs. In this article, we articulate the impact of network virtualization on networks that provide customized services and how a pro- vider’s business can grow with network virtualization. We outline a decision map that allows mapping of applications with technology that is supported in network-virtualization--oriented equipment. Analogies to the world of virtual machines and generic virtualization show that hardware supporting network virtualization will facilitate new customer needs while optimizing the provider network from the cost and performance perspectives. A key conclusion of the article is that growth would yield sizable revenue when providers plan ahead in terms of supporting network-virtualization-oriented technology in their networks. To be precise, providers have to incorporate into their growth plans network elements capable of new service deployments while protecting network neutrality. A simulation study validates our NV-induced model.
Peter Hinrich, P Grosso, Inder Monga, “Collaborative Research Using eScience Infrastructure and High Speed Networks”, Future Generation Computer Systems, April 2, 2015,
Tom Lehman, Xi Yang, Nasir Ghani, Feng Gu, Chin Guok, Inder Monga, and Brian Tierney, “Multilayer Networks: An Architecture Framework”, IEEE Communications Magazine, May 9, 2011,
- Download File: Multilayernetworks2.pdf (pdf: 295 KB)
Neal Charbonneau, Vinod M. Vokkarane, Chin Guok, Inder Monga, “Advance Reservation Frameworks in Hybrid IP-WDM Networks”, IEEE Communications Magazine, May 9, 2011, 59, Issu:132-139,
- Download File: advancereservation3.pdf (pdf: 891 KB)
Inder Monga, Chin Guok, William E. Johnston, and Brian Tierney, “Hybrid Networks: Lessons Learned and Future Challenges Based on ESnet4 Experience”, IEEE Communications Magazine, May 1, 2011,
- Download File: hybridnetworks2.pdf (pdf: 213 KB)
Verónica Rodríguez Tribaldos, Shan Dou, Nate Lindsey, Inder Monga, Chris Tracy, Jonathan Blair Ajo-Franklin, “Monitoring Aquifers Using Relative Seismic Velocity Changes Recorded with Fiber-optic DAS”, AGU Meeting, December 10, 2019,
Qiming Lu, Liang Zhang, Sajith Sasidharan, Wenji Wu, Phil Demar, Chin Guok, John MacAuley, Inder Monga, Se Young Yu, Jim Hao Chen, Joe Mambretti, Jin Kim, Seo Young Noh, Xi Yang, Tom Lehman, and Gary Liu, “BigData Express: Toward Schedulable, Predictable, and High-Performance Data Transfer”, 2018 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS), Institute of Electrical and Electronics Engineers Inc., February 21, 2019, 75-84,
Inder Monga, Chin Guok, John Macauley, Alex Sim, Harvey Newman, Justas Balcas, Phil DeMar, Linda Winkler, Xi Yang, Tom Lehman, “SDN for End-to-end Networked Science at the Exascale (SENSE)”, INDIS Workshop SC18, November 11, 2018,
- Download File: 76kkEi9wqPrVdrGK4bSFdg.pdf (pdf: 907 KB)
The Software-defined network for End-to-end Networked Science at Exascale (SENSE) research project is building smart network services to accelerate scientific discovery in the era of ‘big data’ driven by Exascale, cloud computing, machine learning and AI. The project’s architecture, models, and demonstrated prototype define the mechanisms needed to dynamically build end-to-end virtual guaranteed networks across administrative domains, with no manual intervention. In addition, a highly intuitive ‘intent’ based interface, as defined by the project, allows applications to express their high-level service requirements, and an intelligent, scalable model-based software orchestrator converts that intent into appropriate network services, configured across multiple types of devices. The significance of these capabilities is the ability for science applications to manage the network as a firstclass schedulable resource akin to instruments, compute, and storage, to enable well defined and highly tuned complex workflows that require close coupling of resources spread across a vast geographic footprint such as those used in science domains like high-energy physics and basic energy sciences.
A Mercian, M Kiran, E Pouyoul, B Tierney, I Monga, “INDIRA:‘Application Intent’ network assistant to configure SDN-based high performance scientific networks”, Optical Fiber Communication Conference, July 1, 2017,
M Kiran, E Pouyoul, A Mercian, B Tierney, C Guok, I Monga, “Enabling Intent to Configure Scientific Networks for High Performance Demands”, 3nd International Workshop on Innovating the Network for Data Intensive Science (INDIS) 2016, SC16., November 10, 2016,
- Download File: indis-final-2016.pdf (pdf: 745 KB)
Mariam Kiran, Peter Murphy, Inder Monga, Jon Dugan, Sartaj Baveja, “Lambda Architecture for Cost-effective Batch and Speed Big Data processing”, First Workshop on Data-Centric Infrastructure for Big Data Science (DIBS), October 29, 2015,
- Download File: DIBS-Final-Paper-2015.pdf (pdf: 532 KB)
This paper presents an implementation of the lambda architecture design pattern to construct a data-handling backend on Amazon EC2, providing high throughput, dense and intense data demand delivered as services, minimizing the cost of the network maintenance. This paper combines ideas from database management, cost models, query management and cloud computing to present a general architecture that could be applied in any given scenario where affordable online data processing of Big Datasets is needed. The results are presented with a case study of processing router sensor data on the current ESnet network data as a working example of the approach. The results showcase a reduction in cost and argue benefits for performing online analysis and anomaly detection for sensor data
Adrian Lara, Byrav Ramamurthy, Eric Pouyoul, Inder Monga, “WAN Virtualization and Dynamic End-to-End Bandwidth Provisioning Using SDN”, Optical Fiber Communication Conference 2015, March 22, 2015,
- Download File: OFC-2015-Th1A.2.pdf (pdf: 304 KB)
We evaluate a WAN-virtualization framework in terms of delay and scalability and demonstrate that adding a virtual layer between the physical topology and the end-user brings significant advantages and tolerable delays
Karel van der Veldt, Inder Monga, Jon Dugan, Cees de Laat, Paola Grosso, “Carbon-aware path provisioning for NRENs”, International Green Computing Conference, November 3, 2014,
National Research and Education Networks (NRENs) are becoming keener in providing information on the energy consumption of their equipment. However there are only few NRENs trying to use the available information to reduce power consumption and/or carbon footprint. We set out to study the impact that deploying energy-aware networking devices may have in terms of CO2 emissions, taking the ESnet network as use case. We defined a model that can be used to select paths that lead to a lower impact on the CO2 footprint of the network. We implemented a simulation of the ESnet network using our model to investigate the CO2 footprint under different traffic conditions. Our results suggest that NRENs such as ESnet could reduce their network’s environmental impact if they would deploy energy- aware hardware combined with paths setup tailored to reduction of carbon footprint. This could be achieved by modification of the current path provisioning systems used in the NREN community.
Henrique Rodriguez, Inder Monga, Abhinava Sadasivarao , Sharfuddin Sayed, Chin Guok, Eric Pouyoul, Chris Liou,Tajana Rosing, “Traffic Optimization in Multi-Layered WANs using SDN”, 22nd Annual Symposium on High-Performance Interconnects, Best Student Paper Award, August 27, 2014,
- Download File: hoti2014cam-1-1.pdf (pdf: 1.1 MB)
Wide area networks (WAN) forward traffic through a mix of packet and optical data planes, composed by a variety of devices from different vendors. Multiple forwarding technologies and encapsulation methods are used for each data plane (e.g. IP, MPLS, ATM, SONET, Wavelength Switching). Despite standards defined, the control planes of these devices are usually not interoperable, and different technologies are used to manage each forwarding segment independently (e.g. OpenFlow, TL-1, GMPLS). The result is lack of coordination between layers and inefficient resource usage. In this paper we discuss the design and implementation of a system that uses unmodified OpenFlow to optimize network utilization across layers, enabling practical bandwidth virtualization. We discuss strategies for scalable traffic monitoring and to minimize losses on route updates across layers. We explore two use cases that benefit from multi-layer bandwidth on demand provisioning. A prototype of the system was built open using a traditional circuit reservation application and an unmodified SDN controller, and its evaluation was per-formed on a multi-vendor testbed.
Malathi Veeraraghavan, Inder Monga, “Broadening the scope of optical circuit networks”, International Conference On Optical Network Design and Modeling, Stockholm, Sweden, May 22, 2014,
- Download File: 1569899809.pdf (pdf: 1.7 MB)
Advances in optical communications and switching technologies are enabling energy-efficient, flexible, higher- utilization network operations. To take full advantage of these capabilities, the scope of optical circuit networks can be increased in both the vertical and horizontal directions. In the vertical direction, some of the existing Internet applications, transport-layer protocols, and application-programming interfaces need to be redesigned and new ones invented to leverage the high-bandwidth, low-latency capabilities of optical circuit networks. In the horizontal direction, inter-domain control and management-protocols are required to create a global-scale interconnection of optical circuit-switched networks.
Abhinava Sadasivarao, Sharfuddin Syed, Chris Liou, Ping Pan, Andrew Lake, Chin Guok, Inder Monga, “Open Transport Switch - A Software Defined Networking Architecture for Transport Networks”, August 17, 2013,
- Download File: hots021-ots.pdf (pdf: 353 KB)
There have been a lot of proposals to unify the control and management of packet and circuit networks but none have been deployed widely. In this paper, we propose a sim- ple programmable architecture that abstracts a core transport node into a programmable virtual switch, that meshes well with the software-defined network paradigm while leverag- ing the OpenFlow protocol for control. A demonstration use-case of an OpenFlow-enabled optical virtual switch im- plementation managing a small optical transport network for big-data applications is described. With appropriate exten- sions to OpenFlow, we discuss how the programmability and flexibility SDN brings to packet-optical backbone networks will be substantial in solving some of the complex multi- vendor, multi-layer, multi-domain issues service providers face today.
Baris Aksanli, Jagannathan Venkatesh, Tajana Rosing, Inder Monga, “A Comprehensive Approach to Reduce the Energy Cost of Network of Datacenters”, International Symposium on Computers and Communications, Best Student Paper award, July 7, 2013,
Best Student Paper
Several studies have proposed job migration over the wide area network (WAN) to reduce the energy of networks of datacenters by taking advantage of different electricity prices and load demands. Each study focuses on only a small subset of network parameters and thus their results may have large errors. For example, datacenters usually have long-term power contracts instead of paying market prices. However, previous work neglects these contracts, thus overestimating the energy savings by 2.3x. We present a comprehensive approach to minimize the energy cost of networks of datacenters by modeling performance of the workloads, power contracts, local renewable energy sources, different routing options for WAN and future router technologies. Our method can reduce the energy cost of datacenters by up to 28%, while reducing the error in the energy cost estimation by 2.6x.
Inder Monga, Eric Pouyoul, Chin Guok, “Software Defined Networking for big-data science (paper)”, SuperComputing 2012, November 11, 2012,
- Download File: ESnet-SRS-SC12-paper-camera-ready.pdf (pdf: 1 MB)
University campuses, Supercomputer centers and R&E networks are challenged to architect, build and support IT infrastructure to deal effectively with the data deluge facing most science disciplines. Hybrid network architecture, multi-domain bandwidth reservations, performance monitoring and GLIF Open Lightpath Exchanges (GOLE) are examples of network architectures that have been proposed, championed and implemented successfully to meet the needs of science. Most recently, Science DMZ, a campus design pattern that bypasses traditional performance hotspots in typical campus network implementation, has been gaining momentum. In this paper and corresponding demonstration, we build upon the SC11 SCinet Research Sandbox demonstrator with Software-Defined networking to explore new architectural approaches. A virtual switch network abstraction is explored, that when combined with software-defined networking concepts provides the science users a simple, adaptable network framework to meet their upcoming application requirements.
Jon Dugan, Gopal Vaswani, Gregory Bell, Inder Monga, “The MyESnet Portal: Making the Network Visible”, TERENA 2012 Conference, May 22, 2012,
ESnet provides a platform for moving large data sets and accelerating worldwide scientific collaboration. It provides high-bandwidth, reliable connections that link scientists at national laboratories, universities and other research institutions, enabling them to collaborate on some of the world's most important scientific challenges including renewable energy sources, climate science, and the origins of the universe.
ESnet has embarked on a major project to provide substantial visibility into the inner-workings of the network by aggregating diverse data sources, exposing them via web services, and visualizing them with user-centered interfaces. The portal’s strategy is driven by understanding the needs and requirements of ESnet’s user community and carefully providing interfaces to the data to meet those needs. The 'MyESnet Portal' allows users to monitor, troubleshoot, and understand the real time operations of the network and its associated services.
This paper will describe the MyESnet portal and the process of developing it. The data for the portal comes from a wide variety of sources: homegrown systems, commercial products, and even peer networks. Some visualizations from the portal are presented highlighting some interesting and unusual cases such as power consumption and flow data. Developing effective user interfaces is an iterative process. When a new feature is released, users are both interviewed and observed using the site. From this process valuable insights were found concerning what is important to the users and other features and services they may also want. Open source tools were used to build the portal and the pros and cons of these tools are discussed.
Baris Aksanli, Tajana Rosing, Inder Monga, “Benefits of Green Energy and Proportionality in High Speed Wide Area Networks Connecting Data Centers”, Design, Automation and Test in Europe (DATE), March 5, 2012,
Abstract: Many companies deploy multiple data centers across the globe to satisfy the dramatically increased computational demand. Wide area connectivity between such geographically distributed data centers has an important role to ensure both the quality of service, and, as bandwidths increase to 100Gbps and beyond, as an efficient way to dynamically distribute the computation. The energy cost of data transmission is dominated by the router power consumption, which is unfortunately not energy proportional. In this paper we not only quantify the performance benefits of leveraging the network to run more jobs, but also analyze its energy impact. We compare the benefits of redesigning routers to be more energy efficient to those obtained by leveraging locally available green energy as a complement to the brown energy supply. Furthermore, we design novel green energy aware routing policies for wide area traffic and compare to state-of-the-art shortest path routing algorithm. Our results indicate that using energy proportional routers powered in part by green energy along with our new routing algorithm results in 10x improvement in per router energy efficiency with 36% average increase in the number of jobs completed.
Baris Aksanli, Jagannath Venkatesh, Inder Monga, Tajana Rosing, “Renewable Energy Prediction for Improved Utilization and Efficiency in Data Centers and Backbone Networks”, ( May 30, 2016)
The book at hand gives an overview of the state of the art research in Computational Sustainability as well as case studies of different application scenarios. This covers topics such as renewable energy supply, energy storage and e-mobility, efficiency in data centers and networks, sustainable food and water supply, sustainable health, industrial production and quality, etc. The book describes computational methods and possible application scenarios.
Inder Monga, FABRIC: integration of bits, bytes, and xPUs, JET meeting, March 17, 2020,
- Download File: JET-FABRIC-update-Monga-March-17-2020-1.pdf (pdf: 15 MB)
Presenting NSF-funded FABRIC project to the JET community
Inder Monga, Chin Guok, SDN for End-to-End Networking at Exascale, February 16, 2016,
- Download File: SENSE-Thomas-20160217-on-Web.pdf (pdf: 5.3 MB)
Traditionally, WAN and campus networks and services have evolved independently from each other. For example, MPLS traffic engineered and VPN technologies have been targeted towards the WAN, while the LAN (or last mile) implementations have not incorporated that functionality. These restrictions have resulted in dissonance in services offered in the WAN vs. the LAN. While OSCARS/NSI virtual circuits are widely deployed in the WAN, they typically only run from site boundary to site boundary, and require painful phone calls, manual configuration, and resource allocation decisions for last mile extension. Such inconsistencies in campus infrastructures, all the way from the campus edge to the data-transfer hosts, often lead to unpredictable application performance. New architectures such as the Science DMZ have been successful in simplifying the variance, but the Science DMZ is not designed or able to solve the end-to-end orchestration problem. With the advent of SDN, the R&E community has an opportunity to genuinely orchestrate end-to-end services - and not just from a network perspective, but also from an end-host perspective. In addition, with SDN, the opportunity exists to create a broader set of custom intelligent services that are targeted towards specific science application use-cases. This proposal describes an advanced deployment of SDN equipment and creation of a comprehensive SDN software platform that will help with bring together the missing end-to-end story.
Inder Monga, Plenary Keynote - "Design Patterns: Scaling up eResearch", Web Site, February 9, 2016,
- Download File: ESnet-Monga-eResearch-NZ-Feb2016-Final.pdf (pdf: 9.5 MB)
More details on eResearch Conference at : https://reannz.co.nz/news/eresearch-nz-2016-great-week-queenstown/
Inder Monga, Network Operating Systems and Intent APIs for SDN Applications, Technology Exchange Conference, October 6, 2015,
- Download File: Inder-Monga-Network-OS-Intent-TechX.pdf (pdf: 5.5 MB)
Philosophy of Network Operating Systems and Intent APIs
Inder Monga, ICN roadmaps for the next 2 years, 2nd ACM Conference on Information-Centric Networking (ICN 2015), October 1, 2015,
Panelists: Paul Mankiewich (Cisco), Luca Muscariello (Orange), Inder Monga (ESnet), Ignacio Solis (PARC), GQ Wang(Huawei), Jeff Burke (UCLA)
Abhinava Sadasivarao, Sharfuddin Syed, Ping Pan, Chris Liou, Andy Lake, Chin Guok, Inder Monga, Open Transport Switch: A Software Defined Networking Architecture for Transport Networks, Workshop, August 16, 2013,
- Download File: Monga-HotSDN-SIGCOMM-2013.pptx (pptx: 4 MB)
Presentation at HotSDN Workshop as part of SIGCOMM 2013
Inder Monga, Network Abstractions: The first step towards a programmable WAN, TIP 2013, January 14, 2013,
- Download File: 20130114-monga-networkabstractions.pdf (pdf: 7.4 MB)
University campuses, Supercomputer centers and R&E networks are challenged to architect, build and support IT infrastructure to deal effectively with the data deluge facing most science disciplines. Hybrid network architecture, multi-domain bandwidth reservations, performance monitoring and GLIF Open Lightpath Exchanges (GOLE) are examples of network architectures that have been proposed, championed and implemented successfully to meet the needs of science. This talk explores a new "one virtual switch" abstraction leveraging software-defined networking and OpenFlow concepts, that provides the science users a simple, adaptable network framework to meet their future application requirements. The talk will include the high-level design that includes use of OpenFlow and OSCARS as well as implementation details from demonstration planned for super-computing.
Inder Monga, Introduction to Bandwidth on Demand to LHCONE, LCHONE Point-to-point Service Workshop, December 13, 2012,
- Download File: LHCONE-Bandwidth-on-Demand-Concepts-Mongav2.pptx (pptx: 2.9 MB)
Introducing Bandwidth on Demand concepts to the application community of CMS and ATLAS experiments.
Inder Monga, Software Defined Networking for big-data science, Worldwide LHC Grid meeting, December 2012,
Inder Monga, Eric Pouyoul, Chin Guok, Software Defined Networking for big-data science, SuperComputing 2012, November 15, 2012,
- Download File: Monga-WAN-Switch-SC12SRS.pdf (pdf: 6.5 MB)
The emerging era of “Big Science” demands the highest possible network performance. End-to-end circuit automation and workflow-driven customization are two essential capabilities needed for networks to scale to meet this challenge. This demonstration showcases how combining software-defined networking techniques with virtual circuits capabilities can transform the network into a dynamic, customer-configurable virtual switch. In doing so, users are able to rapidly customize network capabilities to meet their unique workflows with little to no configuration effort. The demo also highlights how the network can be automated to support multiple collaborations in parallel.
Inder Monga, Programmable Information Highway, November 11, 2012,
- Download File: Monga-Network-and-Data-NDMPanel-SC12.pdf (pdf: 2.4 MB)
- Do we need to re-engineer existing tools and middleware software? Elaborate on network management middleware in terms of virtual circuits, performance monitoring, and diagnosis tools.
- What necessary step do we need to implement to benefit from next generation high bandwidth networks? Do you think there will be radical changes such as novel APIs or new network stacks?
I. Monga, E. Pouyoul, C. Guok, Software-Define Networking for Big-Data Science – Arthictectural Models from Campus to the WAN, SC12: IEEE HPC, November 2012,
Inder Monga, Software-defined networking (SDN) and OpenFlow: Hot topics in networking, Masters Class at CMU, NASA Ames, October 2012,
Paola Grosso, Inder Monga, Cees DeLaat, GreenSONAR, GLIF, October 12, 2012,
Inder Monga, Bill St. Arnaud, Erik-Jan Bos, Defining GLIF Architecture Task Force, GLIF, October 11, 2012,
12th Annual LambdaGrid Workshop in Chicago
Inder Monga, Network Service Interface: Concepts and Architecture, I2 Fall Member Meeting, September 2012,
Inder Monga, Architecting and Operating Energy-Efficient Networks, September 10, 2012,
- Download File: Monga-COMBINE-Energy-Efficiency.pdf (pdf: 3.1 MB)
The presentation outlines the network energy efficiency challenges, the growth of network traffic and the simulation use-case to build next-generation energy-efficient network designs.
Inder Monga, Eric Pouyoul, Chin Guok, Eli Dart, SDN for Science Networks, Summer Joint Techs 2012, July 17, 2012,
- Download File: Science-SDN-Monga-JT-07172012.pdf (pdf: 2.6 MB)
Inder Monga, Marching Towards …a Net-Zero Network, WIN2012 Conference, July 2012,
Inder Monga, A Data-Intensive Network Substrate for eResearch, eScience Workshop, July 2012,
Inder Monga, Energy Efficiency starts with measurement, Greentouch Meeting, June 2012,
Inder Monga, ESnet Update: Networks and Research, JGNx and NTT, June 2012,
Eric Pouyoul, Inder Monga, Brian Tierney, Dynamic creation of end-to-end virtual networks for science and cloud computing leveraging OpenFlow/Software Defined Networking, TERENA 2012, May 2012,
C. Guok, I. Monga, IDCP and NSI: Lessons Learned, Deployments and Gap Analysis, OGF 34, March 2012,
Inder Monga, Enabling Science at 100G, ON*Vector Conference, February 2012,
Inder Monga, John MacAuley, GLIF NSI Implementation Task Force Presentation, Winter GLIF Tech Meeting at Baton Rouge, LA, January 26, 2012,
- Download File: NSI-Imp-Taskforce-kick-off-Jan.26.2012.pptx (pptx: 766 KB)
Chaitanya S. K. Vadrevu, Massimo Tornatore, Chin P. Guok, Inder Monga, A Heuristic for Combined Protection of IP Services and Wavelength Services in Optical WDM Networks, IEEE ANTS 2010, December 2010,
C. Guok, I. Monga, Composible Network Service Framework, ESCC, February 2010,
Nicholas A Peters, Warren P Grice, Prem Kumar, Thomas Chapuran, Saikat Guha, Scott Hamilton, Inder Monga, Raymond Newell, Andrei Nomerotski, Don Towsley, Ben Yoo, “Quantum Networks for Open Science (QNOS) Workshop”, DOE Technical Report, April 1, 2019,
ANL – Linda Winkler, Kate Keahey, Caltech – Harvey Newman, Ramiro Voicu, FNAL – Phil DeMar, LBNL/ESnet – Chin Guok, John MacAuley, LBNL/NERSC – Jason Hick, UMD/MAX – Tom Lehman, Xi Yang, Alberto Jimenez, SENSE: SDN for End-to-end Networked Science at the Exascale, August 1, 2015,
- Download File: SENSE-Project-Abstract.pdf (pdf: 124 KB)
Funded Project from DOE